The present invention relates to ecological niche modeling, and more specifically, to inferring ecological niche model input layers from other model input layers.
Ecological niche modeling (ENM) refers to the process of using computer algorithms to predict the distribution of species (e.g., plants, animals, or other living organisms) in geographic space on the basis of a mathematical representation of their known distribution in environmental space. The environment in most cases is represented as climate data (such as temperature and precipitation), however other variables such as soil type, water depth, and land cover can also be used. These models allow for interpolating between a limited number of species' occurrences and are useful in research areas related to conservation biology, ecology, and evolution.
There are a number of motivations for using ENM to understand the range of environmental conditions suitable for a species' survival in the absence of inter-species interactions given a set of environmental parameters. A nascent application of ENM is the projection of species' distributions under climate change scenarios. An understanding of critical species' fundamental niches allows forecasters to predict changes in populations as climate shifts. Another use of ENM is in the prediction of invasive species' habitats in “un-invaded” regions. Invasive species can cause significant damage to the ecosystems that they invade, and thus in turn can have harmful impacts on the humans who rely on those ecosystems. Understanding the fundamental niches of invasive species allows for identification of at risk locations, and can potentially limit the search space for entities interested in seeking out their locations in non-native ecosystems.